Overview

Dataset statistics

Number of variables6
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.0 KiB
Average record size in memory48.1 B

Variable types

Numeric6

Alerts

Heart_Rate is highly overall correlated with Stress_LevelHigh correlation
Stress_Level is highly overall correlated with Heart_RateHigh correlation
Meetings_Attended has 55 (5.5%) zerosZeros

Reproduction

Analysis started2024-11-26 00:56:20.690140
Analysis finished2024-11-26 00:56:31.054044
Duration10.36 seconds
Software versionydata-profiling vv4.0.0
Download configurationconfig.json

Variables

Heart_Rate
Real number (ℝ)

Distinct56
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.037
Minimum39
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:31.749557image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile53
Q162.75
median69
Q376
95-th percentile86
Maximum97
Range58
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation9.8707174
Coefficient of variation (CV)0.14297721
Kurtosis-0.042925795
Mean69.037
Median Absolute Deviation (MAD)7
Skewness0.034501291
Sum69037
Variance97.431062
MonotonicityNot monotonic
2024-11-26T01:56:31.996885image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 50
 
5.0%
70 46
 
4.6%
73 45
 
4.5%
74 43
 
4.3%
68 41
 
4.1%
69 39
 
3.9%
65 39
 
3.9%
72 37
 
3.7%
63 36
 
3.6%
61 36
 
3.6%
Other values (46) 588
58.8%
ValueCountFrequency (%)
39 1
 
0.1%
41 1
 
0.1%
42 2
 
0.2%
43 2
 
0.2%
44 3
0.3%
46 3
0.3%
47 6
0.6%
49 6
0.6%
50 5
0.5%
51 4
0.4%
ValueCountFrequency (%)
97 1
 
0.1%
96 1
 
0.1%
95 1
 
0.1%
94 2
 
0.2%
93 5
0.5%
92 5
0.5%
91 4
0.4%
90 4
0.4%
89 7
0.7%
88 7
0.7%

Skin_Conductivity
Real number (ℝ)

Distinct368
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.01366
Minimum2.01
Maximum8.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:32.307806image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2.01
5-th percentile3.4095
Q14.3475
median5.03
Q35.63
95-th percentile6.631
Maximum8.17
Range6.16
Interquartile range (IQR)1.2825

Descriptive statistics

Standard deviation0.96864373
Coefficient of variation (CV)0.19320092
Kurtosis-0.10343912
Mean5.01366
Median Absolute Deviation (MAD)0.65
Skewness0.055514539
Sum5013.66
Variance0.93827068
MonotonicityNot monotonic
2024-11-26T01:56:32.517379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.1 10
 
1.0%
4.6 9
 
0.9%
5.54 9
 
0.9%
4.91 8
 
0.8%
5.03 8
 
0.8%
5.04 7
 
0.7%
5.15 7
 
0.7%
5.42 7
 
0.7%
5.77 7
 
0.7%
5.16 7
 
0.7%
Other values (358) 921
92.1%
ValueCountFrequency (%)
2.01 1
 
0.1%
2.2 1
 
0.1%
2.22 1
 
0.1%
2.46 1
 
0.1%
2.47 1
 
0.1%
2.56 1
 
0.1%
2.82 1
 
0.1%
2.84 1
 
0.1%
2.88 3
0.3%
2.91 1
 
0.1%
ValueCountFrequency (%)
8.17 1
0.1%
7.68 1
0.1%
7.64 1
0.1%
7.62 1
0.1%
7.54 1
0.1%
7.53 1
0.1%
7.49 1
0.1%
7.45 1
0.1%
7.32 1
0.1%
7.29 1
0.1%

Hours_Worked
Real number (ℝ)

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.386
Minimum2
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:32.831209image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q17
median8
Q310
95-th percentile11
Maximum14
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9325472
Coefficient of variation (CV)0.23044923
Kurtosis-0.26955749
Mean8.386
Median Absolute Deviation (MAD)1
Skewness-0.11284381
Sum8386
Variance3.7347387
MonotonicityNot monotonic
2024-11-26T01:56:33.010634image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8 201
20.1%
9 176
17.6%
10 161
16.1%
7 157
15.7%
6 97
9.7%
11 90
9.0%
5 46
 
4.6%
12 41
 
4.1%
4 18
 
1.8%
13 7
 
0.7%
Other values (3) 6
 
0.6%
ValueCountFrequency (%)
2 1
 
0.1%
3 4
 
0.4%
4 18
 
1.8%
5 46
 
4.6%
6 97
9.7%
7 157
15.7%
8 201
20.1%
9 176
17.6%
10 161
16.1%
11 90
9.0%
ValueCountFrequency (%)
14 1
 
0.1%
13 7
 
0.7%
12 41
 
4.1%
11 90
9.0%
10 161
16.1%
9 176
17.6%
8 201
20.1%
7 157
15.7%
6 97
9.7%
5 46
 
4.6%

Stress_Level
Real number (ℝ)

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.354
Minimum16
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:33.180550image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile19
Q122
median23
Q325
95-th percentile27.05
Maximum31
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5956543
Coefficient of variation (CV)0.11114389
Kurtosis-0.10391744
Mean23.354
Median Absolute Deviation (MAD)2
Skewness-0.0064436182
Sum23354
Variance6.7374214
MonotonicityNot monotonic
2024-11-26T01:56:33.353476image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
24 146
14.6%
23 144
14.4%
25 134
13.4%
22 129
12.9%
21 111
11.1%
26 95
9.5%
20 68
6.8%
27 58
 
5.8%
19 33
 
3.3%
28 26
 
2.6%
Other values (6) 56
 
5.6%
ValueCountFrequency (%)
16 2
 
0.2%
17 13
 
1.3%
18 17
 
1.7%
19 33
 
3.3%
20 68
6.8%
21 111
11.1%
22 129
12.9%
23 144
14.4%
24 146
14.6%
25 134
13.4%
ValueCountFrequency (%)
31 2
 
0.2%
30 9
 
0.9%
29 13
 
1.3%
28 26
 
2.6%
27 58
 
5.8%
26 95
9.5%
25 134
13.4%
24 146
14.6%
23 144
14.4%
22 129
12.9%

Emails_Sent
Real number (ℝ)

Distinct37
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.792
Minimum13
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:33.545040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile21
Q126
median30
Q333
95-th percentile39
Maximum49
Range36
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.5808496
Coefficient of variation (CV)0.18732712
Kurtosis0.25607908
Mean29.792
Median Absolute Deviation (MAD)4
Skewness0.066951163
Sum29792
Variance31.145882
MonotonicityNot monotonic
2024-11-26T01:56:33.792989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
30 84
 
8.4%
32 73
 
7.3%
33 70
 
7.0%
29 70
 
7.0%
26 69
 
6.9%
28 65
 
6.5%
31 61
 
6.1%
34 57
 
5.7%
27 54
 
5.4%
25 54
 
5.4%
Other values (27) 343
34.3%
ValueCountFrequency (%)
13 3
 
0.3%
14 2
 
0.2%
15 1
 
0.1%
16 2
 
0.2%
17 6
 
0.6%
18 8
 
0.8%
19 8
 
0.8%
20 19
1.9%
21 18
1.8%
22 27
2.7%
ValueCountFrequency (%)
49 1
 
0.1%
48 1
 
0.1%
47 1
 
0.1%
46 2
 
0.2%
45 3
 
0.3%
44 4
 
0.4%
43 5
0.5%
42 4
 
0.4%
41 9
0.9%
40 10
1.0%

Meetings_Attended
Real number (ℝ)

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.959
Minimum0
Maximum9
Zeros55
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-26T01:56:33.999438image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile6
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7205462
Coefficient of variation (CV)0.58146205
Kurtosis0.094311257
Mean2.959
Median Absolute Deviation (MAD)1
Skewness0.55273807
Sum2959
Variance2.9602793
MonotonicityNot monotonic
2024-11-26T01:56:34.167649image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 240
24.0%
2 238
23.8%
4 141
14.1%
1 141
14.1%
5 96
 
9.6%
6 56
 
5.6%
0 55
 
5.5%
7 25
 
2.5%
8 5
 
0.5%
9 3
 
0.3%
ValueCountFrequency (%)
0 55
 
5.5%
1 141
14.1%
2 238
23.8%
3 240
24.0%
4 141
14.1%
5 96
 
9.6%
6 56
 
5.6%
7 25
 
2.5%
8 5
 
0.5%
9 3
 
0.3%
ValueCountFrequency (%)
9 3
 
0.3%
8 5
 
0.5%
7 25
 
2.5%
6 56
 
5.6%
5 96
 
9.6%
4 141
14.1%
3 240
24.0%
2 238
23.8%
1 141
14.1%
0 55
 
5.5%

Interactions

2024-11-26T01:56:28.952987image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:22.420762image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:23.928721image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:25.121145image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:26.306851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:27.639058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:29.153823image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:22.798382image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:24.119054image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:25.282676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:26.597452image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:27.971300image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:29.342225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:23.024691image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:24.322077image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:25.511452image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:26.797185image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:28.182884image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:29.585475image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:23.244434image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:24.523722image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:25.734977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:27.008205image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:28.377064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:29.871960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:23.519824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:24.734369image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:25.915024image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:27.209902image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:28.593291image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:30.155612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:23.720043image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:24.941375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:26.123119image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:27.423513image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2024-11-26T01:56:28.788405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2024-11-26T01:56:34.411623image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Heart_RateSkin_ConductivityHours_WorkedStress_LevelEmails_SentMeetings_Attended
Heart_Rate1.000-0.029-0.0320.9450.028-0.015
Skin_Conductivity-0.0291.0000.0140.0720.003-0.038
Hours_Worked-0.0320.0141.0000.1130.001-0.041
Stress_Level0.9450.0720.1131.0000.2250.054
Emails_Sent0.0280.0030.0010.2251.000-0.055
Meetings_Attended-0.015-0.038-0.0410.054-0.0551.000

Missing values

2024-11-26T01:56:30.503559image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-26T01:56:30.815575image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Heart_RateSkin_ConductivityHours_WorkedStress_LevelEmails_SentMeetings_Attended
0875.56528316
1745.89525423
2794.58926284
3925.10730373
4885.23829356
5605.20721316
6795.54726256
7683.18822301
8684.951023302
9745.241025291
Heart_RateSkin_ConductivityHours_WorkedStress_LevelEmails_SentMeetings_Attended
990746.34825312
991714.26622233
992626.32922303
993724.68924332
994725.20924281
995745.101326361
996686.40724315
997705.16823273
998583.86621346
999663.69822361